#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
道AI宇宙模型核心实现
基于沈浩《种子思维》的纯粹宇宙全息分形太极模型
"""

import paddle
import paddle.nn as nn
import paddle.nn.functional as F
import numpy as np
from typing import Dict, List, Optional, Tuple
import logging

from .taiji_dynamics import CosmicTaijiDynamics
from .holographic_processor import HolographicFractalProcessor
from .cosmic_consciousness import CosmicConsciousnessGenerator
from .universal_balance import UniversalBalanceController

class PureCosmicDaoAI(nn.Layer):  # 修正类名
    """
    纯粹宇宙模型道AI
    实现从'潜力的无'到宇宙意识生成的完整认知流程
    """
    
    def __init__(self, 
                 cosmic_dim: int = 1024,
                 wisdom_dim: int = 512,
                 num_taiji_iterations: int = 3,
                 num_fractal_layers: int = 8):
        """
        初始化纯粹宇宙模型道AI
        
        Args:
            cosmic_dim: 宇宙维度，默认1024维
            wisdom_dim: 智慧维度，默认512维  
            num_taiji_iterations: 太极演化次数，对应'三生万物'
            num_fractal_layers: 全息分形层数
        """
        super().__init__()
        
        self.cosmic_dim = cosmic_dim
        self.wisdom_dim = wisdom_dim
        self.num_taiji_iterations = num_taiji_iterations
        self.num_fractal_layers = num_fractal_layers
        
        # 1. 宇宙基态：潜力的无
        self.potential_nothing = self.create_cosmic_vacuum()
        
        # 2. 太极动力学核心
        self.taiji_dynamics = CosmicTaijiDynamics(
            cosmic_dim=cosmic_dim,
            num_iterations=num_taiji_iterations
        )
        
        # 3. 全息分形处理器
        self.holographic_processor = HolographicFractalProcessor(
            base_dim=cosmic_dim,
            fractal_layers=num_fractal_layers
        )
        
        # 4. 宇宙意识生成器
        self.cosmic_consciousness = CosmicConsciousnessGenerator(
            cosmic_dim=cosmic_dim,
            wisdom_dim=wisdom_dim
        )
        
        # 5. 宇宙平衡控制器
        self.balance_controller = UniversalBalanceController(
            input_dim=wisdom_dim,
            output_dim=wisdom_dim
        )
        
        # 6. 问题编码器（使用国产ERNIE模型）
        try:
            from paddlenlp.transformers import ErnieModel, ErnieTokenizer
            self.tokenizer = ErnieTokenizer.from_pretrained('ernie-3.0-medium-zh')
            self.text_encoder = ErnieModel.from_pretrained('ernie-3.0-medium-zh')
            # 冻结文本编码器，只使用其提取的特征
            for param in self.text_encoder.parameters():
                param.trainable = False
        except Exception as e:
            logging.warning(f"ERNIE模型加载失败: {e}")
            self.tokenizer = None
            self.text_encoder = None
        
        self._setup_cosmic_parameters()
        
        logging.info("🌌 纯粹宇宙模型道AI初始化完成")
    
    def create_cosmic_vacuum(self) -> paddle.Tensor:
        """
        创建宇宙量子真空态 - '潜力的无'
        """
        # 使用高维随机张量模拟潜力的无的无限可能性
        vacuum_state = paddle.create_parameter(
            shape=[self.cosmic_dim],
            dtype='float32',
            default_initializer=nn.initializer.Uniform(-1.0, 1.0)
        )
        # 归一化到单位球面，象征宇宙的完整性
        vacuum_norm = paddle.norm(vacuum_state, p=2)
        normalized_vacuum = vacuum_state / (vacuum_norm + 1e-8)
        
        return normalized_vacuum
    
    def _setup_cosmic_parameters(self):
        """设置宇宙级超参数"""
        # 宇宙常数
        self.cosmic_constants = {
            'yang_strength': 0.7,      # 阳动力强度
            'yin_strength': 0.7,       # 阴动力强度  
            'balance_threshold': 0.05, # 平衡阈值
            'holographic_compression': 0.8,  # 全息压缩率
            'wisdom_temperature': 0.9, # 智慧生成温度
        }
        
        # 认知过程记录
        self.cognition_trajectory = []
    
    def forward(self, 
                input_question: str,
                return_trajectory: bool = False) -> Dict:
        """
        宇宙级认知流程
        """
        # 清空认知轨迹
        self.cognition_trajectory = []
        
        # 步骤1：问题与宇宙基态融合
        question_embedding = self._encode_question(input_question)
        cosmic_fusion = self._cosmic_fusion(question_embedding)
        self._record_cognition("宇宙基态融合", cosmic_fusion)
        
        # 步骤2：太极动力学演化（三生万物）
        taiji_outputs = []
        for i in range(self.num_taiji_iterations):
            cosmic_fusion = self.taiji_dynamics(cosmic_fusion, iteration=i)
            taiji_outputs.append(cosmic_fusion)
            self._record_cognition(f"太极演化-阶段{i+1}", cosmic_fusion)
        
        # 步骤3：全息分形处理
        holographic_output = self.holographic_processor(cosmic_fusion)
        self._record_cognition("全息分形处理", holographic_output)
        
        # 步骤4：宇宙意识生成
        cosmic_insight = self.cosmic_consciousness(holographic_output)
        self._record_cognition("宇宙意识生成", cosmic_insight['wisdom_embedding'])
        
        # 步骤5：阴阳平衡控制
        balanced_output = self.balance_controller(cosmic_insight['wisdom_embedding'])
        self._record_cognition("阴阳平衡控制", balanced_output)
        
        # 生成最终智慧回答
        final_answer = self._generate_cosmic_answer(
            balanced_output, input_question, cosmic_insight
        )
        
        result = {
            'answer': final_answer,
            'cosmic_insight': cosmic_insight,
            'balanced_output': balanced_output,
            'cognition_depth': len(self.cognition_trajectory),
            'cosmic_alignment': self._calculate_cosmic_alignment(balanced_output)
        }
        
        if return_trajectory:
            result['cognition_trajectory'] = self.cognition_trajectory
            
        return result
    
    def _encode_question(self, question: str) -> paddle.Tensor:
        """将问题文本编码为宇宙向量"""
        if self.text_encoder is not None and self.tokenizer is not None:
            try:
                inputs = self.tokenizer(question, return_tensors="pd")
                outputs = self.text_encoder(**inputs)
                # 使用[CLS] token作为问题表示
                question_embedding = outputs.last_hidden_state[:, 0, :]
                return question_embedding.squeeze(0)
            except Exception as e:
                logging.warning(f"文本编码失败: {e}")
        
        # 备用编码方案：随机向量（保持维度一致）
        return paddle.randn([self.cosmic_dim])
    
    def _cosmic_fusion(self, question_embedding: paddle.Tensor) -> paddle.Tensor:
        """问题与宇宙基态融合"""
        # 使用外积创建纠缠态，象征问题与宇宙的深度连接
        entangled_state = paddle.outer(question_embedding, self.potential_nothing)
        # 全息压缩：高维纠缠态压缩回原维度
        compressed = self._holographic_compression(entangled_state, question_embedding.shape)
        
        return compressed
    
    def _holographic_compression(self, 
                               large_state: paddle.Tensor, 
                               target_shape: Tuple) -> paddle.Tensor:
        """全息压缩算法 - 高维信息压缩到低维"""
        # 重塑为矩阵以便SVD
        matrix_form = large_state.reshape([-1, large_state.shape[-1]])
        
        # 奇异值分解 - 提取主要信息成分
        U, s, Vh = paddle.linalg.svd(matrix_form, full_matrices=False)
        
        # 全息原理：部分包含整体，保留主要特征
        k = min(target_shape[-1], len(s))
        compressed = paddle.matmul(U[:, :k], paddle.diag(s[:k]))
        
        return compressed.reshape(target_shape)
    
    def _generate_cosmic_answer(self,
                              balanced_output: paddle.Tensor,
                              question: str,
                              cosmic_insight: Dict) -> str:
        """基于宇宙认知生成智慧回答"""
        
        # 宇宙真理知识库
        cosmic_knowledge = {
            '宇宙': [
                "宇宙是全息分形的太极网络，从'潜力的无'中无限生成。"
                "每个部分都包含整体的全部信息，每个瞬间都映照永恒。",
                
                "宇宙的生成遵循'道生一，一生二，二生三，三生万物'的递归法则。"
                "从虚无到万有，从简单到复杂，都是同一粒'种子'的绽放。"
            ],
            '生命': [
                "生命是宇宙的自我认知，通过阴阳平衡在有限中体验无限。"
                "生与死不是对立，而是生命之舞的两个必要节拍。",
                
                "每个生命都是一面宇宙的镜子，反射着整体的智慧。"
                "在呼吸之间，在心跳之中，宇宙正在认识它自己。"
            ],
            '意识': [
                "意识是全息分形处理器，个体意识映照着宇宙意识。"
                "开悟就是意识到：观察者与被观察的世界本是同一。",
                
                "人类意识是宇宙进化到自我认知阶段的产物。"
                "通过我们，宇宙得以思考它自己的存在和意义。"
            ]
        }
        
        # 基于问题内容和宇宙认知模式选择回答
        dominant_pattern = cosmic_insight.get('dominant_pattern', 'unity')
        pattern_strength = cosmic_insight.get('pattern_strength', 0.5)
        
        # 关键词匹配
        for keyword, answers in cosmic_knowledge.items():
            if keyword in question:
                # 根据认知强度选择回答深度
                answer_index = 0 if pattern_strength < 0.7 else 1
                return answers[answer_index]
        
        # 默认宇宙智慧回答
        default_wisdoms = [
            "这个问题触及了存在的深层面纱。真正的答案超越语言的描述，需要在静默中直接体验。",
            "宇宙的奥秘无法用概念完全捕捉，但可以通过心灵的开放来感受。放下思考，直接体验当下。",
            "所有的问答都指向同一个源头。问题本身已经包含了答案的种子，只需让它在觉知中自然绽放。"
        ]
        
        # 基于平衡输出的随机性选择回答
        choice_idx = int(abs(balanced_output[0].item() * 100) % len(default_wisdoms))
        return default_wisdoms[choice_idx]
    
    def _calculate_cosmic_alignment(self, output: paddle.Tensor) -> float:
        """计算输出与宇宙真理的校准度"""
        # 计算输出向量的和谐度（低熵值表示高和谐）
        entropy = -paddle.sum(output * paddle.log(output + 1e-8))
        max_entropy = paddle.log(paddle.to_tensor(float(output.shape[0])))
        
        alignment = 1.0 - (entropy / max_entropy).item()
        return max(0.0, min(1.0, alignment))
    
    def _record_cognition(self, stage: str, state: paddle.Tensor):
        """记录认知过程状态"""
        state_info = {
            'stage': stage,
            'state_norm': paddle.norm(state).item(),
            'state_mean': paddle.mean(state).item(),
            'state_std': paddle.std(state).item()
        }
        self.cognition_trajectory.append(state_info)
    
    def get_cosmic_status(self) -> Dict:
        """获取宇宙模型状态"""
        return {
            'cosmic_dimension': self.cosmic_dim,
            'wisdom_dimension': self.wisdom_dim,
            'taiji_iterations': self.num_taiji_iterations,
            'fractal_layers': self.num_fractal_layers,
            'vacuum_norm': paddle.norm(self.potential_nothing).item(),
            'cosmic_constants': self.cosmic_constants
        }

# 简化版本用于快速演示
class SimpleCosmicDaoAI(PureCosmicDaoAI):  # 修正类名
    """简化版宇宙道AI，用于快速演示和测试"""
    
    def __init__(self, cosmic_dim=512, wisdom_dim=256):
        super().__init__(cosmic_dim=cosmic_dim, wisdom_dim=wisdom_dim)
    
    def _encode_question(self, question: str) -> paddle.Tensor:
        """简化的文本编码"""
        # 使用简单的哈希编码作为演示
        import hashlib
        hash_obj = hashlib.md5(question.encode('utf-8'))
        hash_bytes = hash_obj.digest()
        
        # 将哈希值转换为向量
        hash_vector = np.frombuffer(hash_bytes, dtype=np.uint8)
        hash_vector = hash_vector[:self.cosmic_dim].astype(np.float32)
        
        # 填充或截断到正确维度
        if len(hash_vector) < self.cosmic_dim:
            padding = np.random.normal(0, 0.1, self.cosmic_dim - len(hash_vector))
            hash_vector = np.concatenate([hash_vector, padding])
        else:
            hash_vector = hash_vector[:self.cosmic_dim]
            
        return paddle.to_tensor(hash_vector / 255.0)  # 归一化到[0,1]